The COVID-19 situation continues to evolve rapidly. All data and statistics are based on publicly available data at the time of publication.
If there’s one thing the COVID-19 pandemic has shown about health writing, it’s the importance of managing your reader’s expectations when writing about clinical trials. Or to put it another way, health and science writers should avoid overhyping the results of new coronavirus studies.
With over 2 million coronavirus cases and over 113,000 COVID-19 deaths just in the United States (as of June 12), interest in finding effective treatments for COVID-19 is intense. To date, over 2,000 COVID-19 studies were registered on ClinicalTrials.gov, with over 1,100 treatment studies.
In spite of global research efforts, so far no published, peer-reviewed studies have shown that any specific treatments can reduce the risk of dying from COVID-19. Physicians currently rely on supportive care to help people with COVID-19.
However, there are some signs of hope. The results from a clinical trial of remdesivir, published in late May in the New England Journal of Medicine, showed that this antiviral reduced recovery time in patients. Still, it’s not clear yet whether the drug can reduce patient mortality.
Over the coming weeks and months, more results from ongoing clinical trials — hopefully promising — will be published. Waiting for these results, though, is not easy, especially when public interest in COVID-19 remains high.
COVID-19 Shifts How Research Is Shared
COVID-19 has changed many aspects of our lives — from how we get our food to how we interact with others in public — but it has also shifted how the public finds out about the latest research.
Before the pandemic, news media mainly reported on clinical trials once the results had been published in a peer-reviewed journal. Journalists had early access to the final papers, but these were usually under strict embargo, meaning the news stories couldn’t be published until a certain date and time.
Now journalists are reporting more often about preliminary results from COVID-19 clinical trials. Some of these are published as non-peer-reviewed papers on preprint servers such as medRxiv and bioRxiv. Other early results are “leaked” by researchers or other study staff, as happened recently with one of the remdesivir trials.
Complicating matters, many of these preliminary results are being shared on social media, sometimes by scientists qualified to discuss the results, but often by “armchair epidemiologists” and even by politicians such as President Donald Trump.
Social media will likely continue to play a role in educating people about COVID-19 clinical trials — for better or for worse. However, this makes it even more important for health and science writers to be careful when writing about clinical trials.
Drs. Howard Bauchner and Phil B. Fontanarosa, two editors of JAMA, recently offered their suggestions for how “clinicians, the public, and politicians [can] understand the results of these much-anticipated and critically needed [COVID-19] clinical trials.”
These are also useful guidelines for journalists writing about COVID-19 research, as well as any clinical trial.
Writing About Clinical Trials Responsibly
Not all research is created equal. Bauchner and Fontanarosa recommend that journalists, physicians, and the general public keep in mind the following clinical trial characteristics when thinking about the results.
Use of a control group. In a randomized controlled trial (RCT) — the “gold standard” of clinical research — patients are randomly assigned to either an intervention group or a control group.
The control group doesn’t receive the treatment or participate in the intervention. Instead, people in that group may receive an inactive placebo (such as in a drug trial) or undergo only the standard treatment.(such as in an intervention trial).
If a control group isn’t used, it is more difficult to know if the benefits are due to the treatment, drug, or intervention or if they occurred by chance.
Simultaneous treatments. In some clinical trials, patients may receive multiple investigational medications, either at the same time or at various times throughout the disease process. This can make it challenging to know if the benefits are due to one of the medications or the combination.
Study size. Many COVID-19 clinical trials, especially observational ones, have been relatively small. While these studies may have enough patients to show if a drug or treatment has some effect, the trial may leave some questions unanswered.
Bauchner and Fontanarosa point out that people with severe COVID-19 can have widely varying symptoms. As a result, one treatment may benefit certain patients more than others, depending on the severity of their symptoms or when during their disease process the treatment is given.
So while a smaller study may show that a treatment is effective for patients with COVID-19, there may not be enough participants enrolled for researchers to know which groups of patients would benefit the most or the best time to give the treatment.
Outcomes of the trial. The goal of most COVID-19 clinical trials is to reduce mortality, but not all studies are able to answer that question. Instead, many measure outcomes such as time to recover, reduction in the need for mechanical ventilation, or decrease in the coronavirus viral load.
“It will be important to objectively assess and accurately describe the outcomes from ongoing trials,” write Bauchner and Fontanarosa, “and what the results potentially mean in terms of improving overall survival.”
Absolute treatment benefit. While a news story headline such as “Drug Improves survival in Severe COVID-19 Patients” is click-worthy, it doesn’t answer an important question: how much of a benefit was seen?
If a COVID-19 treatment reduces mortality by only 5 percent to 10 percent (the absolute difference), at least 10 to 20 people would need to be treated in order for one person to benefit from the treatment. This is known as the Number Needed to Treat (NNT). A smaller absolute benefit would have a greater NNT.
“This remains a challenging issue for clinicians and patients to understand,” write Bauchner and Fontanarosa. “Given these likely numbers needed to treat, most [COVID-19] patients will not benefit from even a successful treatment.”
They also point out that a successful treatment does not mean that patients are “cured” of COVID-19. Sometimes patients just see a reduction in how long they are on a ventilator or how many days they spend in the hospital.
Prevention versus treatment. Many COVID-19 clinical trials involve treatments for people who are already hospitalized. However, an estimated 81 percent of people will have only mild to moderate symptoms, so those who end up in the hospital are usually the sickest.
While a successful COVID-19 treatment may reduce mortality in people who have been hospitalized, it may not keep people who have been exposed to the virus from needing to be hospitalized. Hydroxychloroquine is being investigated for that, but so far the results have not been promising.
A successful COVID-19 treatment may also not slow the spread of the coronavirus. For that, we still need public health strategies such as social distancing, handwashing, testing, quarantines, and contact tracing.
As a result, “the findings of rigorous clinical trials of vaccines and possible other therapies will be essential in determining how to effectively prevent COVID-19,” write Bauchner and Fontanarosa.
Writing About COVID-19 Going Forward
Until a safe and effective vaccine against the coronavirus is widely available, COVID-19 won’t be going away anytime soon. But with the number of cases declining in some parts of the world, attention has shifted towards blunting future waves and responding more effectively when they do occur.
In the meantime, research on COVID-19 — including vaccine trials — will continue, which means health and science writers will continue writing about these clinical trials well into the future. As they do, they will need to make sure they avoid overhyping the results.
“Because much of the focus is now on preventing recurrence of the pandemic, it will be important for investigators, journals, and the media to accurately report the results of the studies responsibly and what they mean both for individuals and for population health,” write Bauchner and Fontanarosa.
